If you have not yet installed macrel, see install.
Macrel uses a subcommand interface. You run
macrel COMMAND ...with the COMMAND specifying which components of the pipeline you want to use.
peptides: to classify a fasta containing peptide sequences in a fasta file,
contigs: to input pre-assembled contigs in a fasta file,
reads: to input reads in fastQ format (Macrel accepts single- and paired-end reads),
abundance: to measure abundance of a peptides fasta file using a given fastQ file,
get-smorfs: to predict small genes from a contigs fasta file.
Mandatory input flags
--out: Folder destination to output [for all subcommands]
--file-output: Can be used in the
get-smorfssubcommand to output just the final file. If this is used,
--outis no longer mandatory
--fasta: Path to the input FASTA file. This is used in both the
peptidessubcommands (where the file is expected to contain short amino-acid sequences) and in the
contigs/get-smorfssubcommands (where the file is expected to contain longer nucleotide contigs)
--reads1/--reads2: Path to the input FastQ files [for
-t): Specify the number of cpus used
--cluster: Pre-cluster the smORFs (at 100%% identity) to avoid repeats
--tag: If used, then all the output files will incorporate it.
--mem: Used during assembly to specify the percent of RAM used (1-0)
--tmpdir: Temporary directory to use (default:
$TMPDIRin the environment or /tmp)
--force: Potentially over-write existing output files
--keep-fasta-headers: Keep complete FASTA headers [get-smorfs command]
--keep-negatives: Output a table with all sequences (default is to only output putative AMPs)
macrel --version will show the version of macrel installed.
To run these examples, first download the example sequences from github, or by running:
The main output file generated by Macrel consists of a table with 6 columns containing the: sequence access code, peptide sequence, classification of peptide accordingly (cationic or anionic) and structure (linear or disulfide bond forming), the probability associated with the AMP prediction, hemolytic activity prediction and probability associated to hemolytic activity prediction. All peptides outputted in this table are considered predicted AMPs (p > 0.5) by Macrel, although peptides predicted with probabilities closer to 1 are more likely to be active. Similarly, the hemolytic activity is more likely to be verified in those peptides with probabilites associated to the prediction closer to 1.
Note that there is not a general rule to find true AMPs or hemolytic peptides, then peptides predicted with probabilites around 0.5 also can show activity. In our tests during training true peptides could be found with probabilities ranging from 0.5 to 1, although most of them with probabilites above 0.6
To run Macrel on peptides, use the
macrel peptides \ --fasta example_seqs/expep.faa.gz \ --output out_peptides \ -t 4
In this case, we use
example_seqs/expep.faa.gz as the input sequence. This should
be an amino-acid FASTA file. The outputs will be written into a folder called
out_peptides, and Macrel will 4 threads. An example of output using
this mode can be found at
To run Macrel on contigs, use the
macrel contigs \ --fasta example_seqs/excontigs.fna.gz \ --output out_contigs
In this example, we use the example file
excontigs.fna.gz which is a FASTA
file with nucleotide sequences, writing the output to
An example of output using this mode can be found at
Additionally to the prediction table, this mode also produces two files containing
general gene prediction information in the contigs and a fasta file containing the
predicted and filtered small genes (<= 100 amino acids).
To run Macrel on paired-end reads, use the
macrel reads \ -1 example_seqs/R1.fq.gz \ -2 example_seqs/R2.fq.gz \ --output out_metag \ --outtag example_metag
The paired-end reads are given as paired files (here,
example_seqs/R2.fq.gz). If you only have single-end reads, you can omit
-2 argument. An example of outputs using this mode can be found at
Additionally to the prediction table, this mode also produces a contigs fasta file,
and the two files containing general gene prediction coordinates and a fasta file
containing the predicted and filtered small genes (<= 100 amino acids).
To run Macrel to get abundance profiles, you only need the short reads file
and a reference with peptide sequences. Use the
macrel abundance \ -1 example_seqs/R1.fq.gz \ --fasta example_seqs/ref.faa.gz \ --output out_abundance \ --outtag example_abundance
This mode returns a table of abundances containing two columns, the first with the
name of the AMPs and the second with the number of reads mapped back to each peptide
using the given reference. An example of this output using the example file can be found